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A damped diffusion framework for financial modeling and closed-form maximum likelihood estimation

机译:用于财务建模和封闭式最大似然估计的阻尼扩散框架

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Asset price bubbles can arise unintentionally when one uses continuous-time diffusion processes to model financial quantities. We propose a flexible damped diffusion framework that is able to break many types of bubbles and preserve the martingale pricing approach. Damping can be done on either the diffusion or drift function. Oftentimes, certain solutions to the valuation PDE can be ruled out by requiring the solution to be a limit of martingale prices for damped diffusion models. Monte Carlo study shows that with finite time-series length, maximum likelihood estimation often fails to detect the damped diffusion function while fabricates nonlinear drift function. An alternative method based on ATt-Sahalia's specification test on parametric models is proposed.
机译:当人们使用连续时间扩散过程对财务数量进行建模时,资产价格泡沫可能会无意中出现。我们提出了一种灵活的阻尼扩散框架,该框架能够打破许多类型的泡沫并保留the定价方法。可以对扩散功能或漂移功能进行阻尼。通常,可以通过要求解决方案是阻尼扩散模型的mar价格极限来排除估值PDE的某些解决方案。蒙特卡洛研究表明,在有限的时间序列长度下,最大似然估计常常无法检测出阻尼扩散函数,而制造了非线性漂移函数。提出了一种基于ATt-Sahalia参数模型规范测试的替代方法。

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